Word Embeddings: a vector with 300 dimensions averaging vector representations of the words in the tweet using Word2Vec [1]}. The Word2Vec model for each of the eight folds is trained from the collection of tweets pertaining to the seven events in the training set, so that the event (and the vocabulary) in the test set is unknown.

